A conceptual similarity and correlation discrimination method based on HowNet
| Autor: | Yangli Jia, Zhenling Zhang, Yunnian Ding |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry 0211 other engineering and technologies Pattern recognition 02 engineering and technology Engineering (General). Civil engineering (General) Correlation 020303 mechanical engineering & transports 0203 mechanical engineering Similarity (network science) hownet 021105 building & construction Artificial intelligence relevance natural language processing TA1-2040 business similarity |
| Zdroj: | MATEC Web of Conferences, Vol 309, p 03020 (2020) |
| Popis: | The similarity and correlation analysis of word concepts has a wide range of applications in natural language processing, and has important research significance in information retrieval, text classification, data mining, and other application fields. This paper analyzes and summarizes the information of sememes relationship through the definition of words in HowNet and proposes a method to distinguish the similarity and correlation of words. Firstly, using a combination of the part of speech and sememes to distinguish the similarity and correlation between words concept. Secondly, the similarity and correlation calculation results between vocabulary concepts are used to further optimize the judgment results. Finally, the similarity and correlation distinction and discrimination between vocabulary concepts are realized. The experimental results show that the method reduces the complexity of the algorithm and greatly improves the work efficiency. The semantic similarity and correlation judgment results are more in line with the human intuitive experience and improve the accuracy of computer understanding of natural language. which provides an important theoretical basis for the development of natural language. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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